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F
Published in Philip A. Laplante, Comprehensive Dictionary of Electrical Engineering, 2018
first order system the system that can be described by a linear first-order difference equation. The output of the first-order system y(n) is equal to a linear combination of the past output value y(n - 1) and the input value x(n), i.e., y(n) = x(n) + y(n - 1) first-fit memory allocation a memory allocation algorithm used for variable-size units (e.g., segments). The "hole" selected is the first one that will fit the unit to be loaded. This hole is then broken up into two pieces: one for the process and one for the unused memory, except in the unlikely case of an exact fit, there is no unused memory. first-in-first-out (FIFO) a queuing discipline whereby the entries in a queue are removed in the same order as that in which they joined the queue. first-in-last-out (FILO) a queuing rule whereby the first entries are removed in the opposite order as that in which they joined the queue. This is typical of Stack structures and equivalent to lastin-first-out (LIFO). first-swing stability criterion to determine transient stability by use of the swing equation. The rotor angle immediately following a severe disturbance usually increases. The criterion states that if the rotor angle swings back and decreases a short time after the disturbance, then the system is first-swing stable. Fisher information a quantitative measurement of the ability to estimate a specific set of parameters. The Fisher information J () is
Introduction
Published in Vlad P. Shmerko, Svetlana N. Yanushkevich, Sergey Edward Lyshevski, Computer Arithmetics for Nanoelectronics, 2018
Vlad P. Shmerko, Svetlana N. Yanushkevich, Sergey Edward Lyshevski
Two special but very often used types of register with shift function are firstin-first-out (FIFO) and last-in-first-out (LIFO) registers. The FIFO register acts as a pipeline, or a queue, as the data enter the register sequentially, bit by bit, and exits sequentially, starting from the first bit entered. The LIFO register acts as a stack, since the bit pushed first into the LIFO is fetched last. FIFO and LIFO registers can form wordwide arrays. The control of such arrays is not trivial, and requires additional control circuitry.
A hierarchical priority task scheduling with QoS satisfaction for cloud storage
Published in Amir Hussain, Mirjana Ivanovic, Electronics, Communications and Networks IV, 2015
Qingying Lin, Yuelong Zhao, Wei Chen, Ping Zhong
Because cloud computing and grid computing have great similarities, the scheduling algorithms for cloud computing and cloud storage system are improved from these algorithms. The traditional task scheduling algorithms aim to increase the system throughput, for example, traditional Min-Min and Max-Min scheduling algorithms, some heuristic algorithms such as Ant Colony (AC) (Song et al. 2011) scheduling algorithm, Genetic Algorithm (GA) (Ge & Wei 2010), Particle Swarm Optimization (PSO) scheduling algorithm. With deeper application and research, the only emphasis on the system throughput has been unable to meet the needs of practical applications. Therefore, the load balancing strategy is emphasized on the basis of the sacrifice of some system throughput. In addition, some major cloud computing providers, according to the characteristics of their own resources, will adopt different scheduling strategies. Some of more famous cloud computing platforms, like IBM, Google, Yahoo, they mainly take advantage of master-slave scheduling model, the task scheduling of the whole system is controlled by a master node. Early master node scheduling uses the FIFO scheduling algorithm that user tasks are submitted to the only queue. Slave node asks the master node for the allocation of tasks in their free time. The advantages of the FIFO are that it is very simple to implement, fast in the scheduling process and occupies fewer resources. The disadvantage is that it is unable to guarantee the quality of service for some small tasks which require high real-time. Considering the problem of FIFO, Yahoo has developed the Capacity Scheduler (Polo et al. 2010). This algorithm adopts multiple queues, and each queue is assigned a certain amount of system resources. Idle resources can be allocated to the heavy load queue, which means supporting task priority. On the one hand, there are some advantages of supporting multi-task parallel execution, such as an increase in resource utilization and improvement in the efficiency of task execution. On the other hand, the disadvantage is that users need to know a lot of information of the system resource, so that they can set and choose the queue. Moreover, FIFO scheduling is still employed within any queue. In addition, for the master-slave scheduling model, the researchers design the scheduling algorithm to adapt to users with special needs, such as a Deadline Scheduler scheduling algorithm for real-time tasks. Deadline Scheduler obtains resource values through the task running schedule and time remaining dynamic adjustment of the task, so that the task could be completed as far as possible within the deadline. These scheduling algorithms only
Design of yarn tension self-adaptive control system on warp knitting machine
Published in The Journal of The Textile Institute, 2023
The real-time performance and stability of the system are the most important parts to realize the dynamic programming of the tension regulation rod. According to the motion characteristics of the warp knitting machine, a double FIFO dynamic interpolation motion planning method is designed, as shown in Figure 12. FIFO is the abbreviation of First Input First Output, which is a first-in-first-out data buffer. The motion control system uses two independent FIFOs to store the tension rod motion trajectory data of two different courses. At the same time, the two FIFOs can be switched at high speed under the state of motion. When the system finishes executing the FIFO1 trajectory, it automatically and efficiently switches to FIFO2 to execute the next horizontal tension lever to control trajectory data. In the meantime, the executed FIFO1 trajectory data is cleared, and the new course control rod trajectory data is loaded, and the dual FIFO dynamic interpolation motion planning is implemented alternately.
Reinforcement learning for robotic flow shop scheduling with processing time variations
Published in International Journal of Production Research, 2022
For the comparison of the proposed RL algorithm, we briefly explain the FIFO rule and RS. In general, when there are processing time variations so that no exact processing times are given, dispatching rules are widely used because optimisation approaches are not applicable (Crist and Uzsoy 2011). Regarding dispatching rules, Panwalkar and Iskander (1977) provides a survey, which classifies them into five groups; Rules related to processing times, related to due dates, related to setup times, related to costs, and related to arrival times and random. The rules related to processing times, such as SPT and shortest remaining processing time (SRPT), are not applicable to our problem because the actual processing times are unknown until they are finished. The rules related to due dates, setup times, or costs are not relevant to our study. Lastly, the rules related to arrival times and random include FIFO, Random (select jobs in a random order), and last-in-first-out (LIFO). Among them, when the makespan measure is considered, FIFO is an appropriate rule because it tries to reduce the waiting times of machines by sequencing tasks based on their available times.
Reactive scheduling approach for solving a realistic flexible job shop scheduling problem
Published in International Journal of Production Research, 2021
B. Mihoubi, B. Bouzouia, M. Gaham
JES: It is a jobs vector where each of these positions indicates a rank number associated with the specified job.The PDR assigned for each machine, and they are: J-SPT: Job that has the Shortest operation Processing Time.J-LPT: Job that has the Longest operation Processing Time.FIFO: First Input First Output.LIFO: Last Input First Output.The PDR of jobs: each job selects machine according to: RP1: Least loaded machine, including the shortest transportation time between a job, placed in a location machine and its destination machine (min of the sum (LLM,STT)).M-SPT: Machine that achieves the Shortest operations Processing Time.M-LPT: Machine that achieves the Longest operations Processing Time.LLM: Least Loaded Machine.STT: Shortest Transportation Time between a job, placed in a location machine and its destination machine.